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Reconstructing Non-stationary Articulated Objects in Monocular Video using Silhouette Information

Reconstructing Non-stationary Articulated Objects in Monocular Video using Silhouette Information. Saad M. Khan and Mubarak Shah University of Central Florida, Orlando, FL, USA. ICPR 2008 Reporter: Hsieh, Chia-Hao Date: 2009/09/07.

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Reconstructing Non-stationary Articulated Objects in Monocular Video using Silhouette Information

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  1. Reconstructing Non-stationary Articulated Objects in Monocular Video usingSilhouette Information Saad M. Khan and Mubarak Shah University of Central Florida, Orlando, FL, USA. ICPR 2008 Reporter: Hsieh, Chia-Hao Date: 2009/09/07

  2. Reconstructing Non-stationary Articulated Objects in Monocular Video using Silhouette Information Introduction • Silhouette fusion (combine color and silhouette image) • Blurred occupancy images • Motion deblurring of the occupancy images • Virtual hull reconstruction by the de-blurred images Blurred Occupancy Images

  3. Outline • Scene Occupancies • Temporal Occupancy Points (TOP) • Building Blurred Occupancy Images • Motion Deblurring • Final Reconstruction

  4. temporal occupancy :the fraction of total time instances Scene point Pi is guaranteed to be occupied in Scene Occupancies determines

  5. Temporal Occupancy Points (TOP) views from a monocular camera sequence (flyby) Move left arm projection projection Temporal bounding edges

  6. Temporal Occupancy Points (TOP) • No complete camera calibration at each time instant  no 3D information • Purely image-based approach • Obtain the projections (images) of the TOP in each view

  7. Temporal Occupancy Points (TOP) Point to point transform by homography γ ground plane reference system

  8. Building Blurred Occupancy Images For each silhouette image, store value τ at projected locations of TOP in each blurred occupancy images

  9. Motion Deblurring Blurred occupancy image = unblurred occupancy image CONVOLUTE blur kernel PLUS noise Blur kernel also known as the point spread function (PSF) User specifies different crop regions of the blurred occupancy images each with uniform motion, which are then restored separately

  10. Final Reconstruction • Using the method of [7]A Homographic Framework for the Fusion of Multi-view Silhouettes. IEEE ICCV 2007.

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